Presentation Transcript

Clinical Data Management and Case Report Form :

Clinical Data Management and Case Report Form by
Jen-Pei Liu, Ph.D. Professor
Division of Biometry
Department of Agronomy
National Taiwan University
and
Division of Biostatistics and Bioinformatics
National Health Research Institutes

I. Introduction :

I. Introduction Clinical Data Management
To provide consistency, accuracy and validity of clinical data in timeliness and cost-effective manner to support of conclusion on efficacy, safety, quality of life and pharmacoeconomic assessment of a pharmaceutical product.

Case Report Form :

Case Report Form Objectives
To collect the clinical data outlined in the protocol so that the clinical research questions can be answered
To collect information related to efficacy, safety, quality of life, and pharmacoeconomics
To minimize the clinical trial processing and to maximize its efficiency
Easy to use for all members of clinical study team

Slide 6:

Needs of CRF Users (1)
The needs of each member in the clinical study team using CRFs may be different
Each member should be considered
Investigators
Study coordinators/Study nurses
Clinical research associate (CRA)
Data entry personnel
Data reviewers
Database programmers
Statisticians

Slide 7:

Needs of CRF Users (2)
Investigators/Study Nurses
easy to complete and CRF's are organized based on how data are generated
Clinical Research Associates
easy for review
blanks and inconsistency can be easily spotted
Data Entry Personnel
Easy for entry
Data are lined up on one side
Not too busy
easily readable

Slide 8:

Needs of CRF Users (3)
Database Programmers
Standardization of CRF's
Easy copying between applications
Statisticians
Arranged in a logical and analytical order
Easy for merging and grouping

Slide 9:

Standardization of CRF's (1)
Collect similar data across studies in a standard manner as much as possible
Easy to computerize
Easy to integrate
Easy to review
Easy to validate
Improve efficiency
Improve accuracy
Improve quality

Slide 12:

Slide 13:

Guidelines for Designing CRFs (1)
Same data never collect twice
Collection of the same data will create inconsistency and unnecessary work for data checking
Example
Collect age and date of birth
Vital sign including blood pressure in an anti-hypertensive trial
Toxicity and Adverse events

Slide 14:

Guidelines for Designing CRFs (2)
Do not collect leading or open-ended question if
data is needed for summarization
need detailed information and consistency
Do not require unnecessary computation
Only to collect raw data and only ask investigators/study nurses to do calculations on data they need to use during the study

Slide 16:

Guidelines for Designing CRFs (4)
If findings were not present or test was not done, the CRF should indicate it
Use "Not Done" or "Not Applicable"
Do not assume that a blink on CRF implies no findings
Easy to find data on CRF
Minimizing the page turning
No tedious transcription
To collect data that allows for the most efficient computerization
Use pre-codes for data that may need to be summarized or searched
Use check boxes whenever possible

Clinical Data Management :

Clinical Data Management Concept of Data Management
For a single study, it starts from the protocol development and ends with completion of the study
For a clinical development program, it starts from the very first protocol until the approval of the pharmaceutical product if it gets approved
A high quality database of a clinical trial reflects a well designed and a well-conducted study which generated accurate and reliable inference to the targeted patient population

Slide 76:

Standard statement for data management in a protocol
Complete Case Report Forms will be reviewed by both clinical and data management personnel. Data will be entered directly into the database and verifying using a database management system that provides formatted screens, range checking, and relational consistency checking. Subject-oriented edit listings will be generated for comparison to the database, a complete audit trail of the corrections, as well as any coding procedures, will be retained as an integrated part of the study record.

Slide 86:

Slide 87:

Revision
Protocol
Affect the statistical analysis
Sample size, power, Design, objectives, etc.
Projective statistician － Review and assessment of the changes
CRF
Review the changes
New form － date of creation on the bottom of the form Database or data entry screens
Documentation in study workbook

Database Development and Validation :

Objective
Design, generate, and validate a database
Scope
Database development for all clinical protocol Database Development and Validation

Flow and Tracking of CRF :

Slide 96:

Responsibility
Retrieval from Center：Clinical Research
Logging into tracking system：Biostatistics
Patient Status
Receipt and processing of CRF
Procedure (1)
Retrieval of CRF from Center by Clinical Research
Patient identification number － Clinical Research
Corrections on all 3 copies (NCR)
2 photocopies from the original (non-NCR)

Data Entry :

Slide 101:

Responsibility：Biostatistics
Accurate is paramount
No interpretation of investigators intent
100% Database CRF
Procedures (1)
CRF logged into the tracking system
Order：First in, First out
No CRF should be left on a desk overnight
All CRF’s returned to the files
Files locked at the end of each day

Slide 102:

Procedures (2)
Double entered and verified
Entry：Consistent throughout each study via clinical trial data dictionary
All data in the designated areas must be entered
All data in non-designated areas must not be entered
Data Assistant
CRF form the 1st entry file
Password into data entry system(Study specific)
After entry stamp“1st ENTRY ” on back of CRF on each page with the current Date and put the CRF in the verification (2nd ENTRY) file

Slide 103:

Procedures (3)
Different Data Assistant：Data verification
CRF form the 2nd entry file
Program checks the 1st and 2nd entry
Display any mismatched fields
Make appropriate corrections to the database based on the CRF
Stamp “2nd ENTRY ” and current date
Put the CRF in the completed file.

Slide 104:

Procedures (4)
Run the edit program
Pre-specified conditions for quality and accuracy
Output form the edit program should be reviewed and sent to Clinical Research.
Data quality assurance audit
Do NOT write or make anything on the face of CRF.

Slide 105:

Revision
No corrections will be made until the changes have been documented according to the appropriate correction procedure.
For blinded studies, data entry and revision should be performed in a blinded fashion.

Data Validation and Correction Processing :

Slide 107:

Errors
Data entry error?
Yes  systematic problem
No  data discrepancy form  logged into the tracking system  CRAs  investigators CRAs  data operators  corrections to database  tracking system
Corrected CRFs be on top of the original version
Audit trails
The value before and after, date of the change and persons

Slide 110:

Comparison of printout with CRFs and corrections
Discrepancy – Data Audit
Goal – overall error rate <0.1%
Data Audit Summary Report
Number of fields checked
Number of errors found
A total count of investigators, patients, visits, and CRF pages in the study
A total count of investigators, patients, visits, and CRF pages in the study workbook